Main research
Column
Intro page about
How we sampled people, general construction and explanation of Gold-MSI and our genre/gender questions and announing setup of our research
Some graphs with general info about gender, sophistication scores and genre preferences
Under construction
Column
The LCA
Latent Class Analysis or LCA is a psychometric method in which participants are grouped based on how likely they would respond positive to a certain survey item, in our case a song snippet that is either beautiful or not. After running the results of our 119 participants through the LCA, it appeared that only a 3-class model fitted the data appropriately, so that is what you see in the table.
At the top of the table, the currently unnamed classes are visible. The row with class proportions shows how many of our participants where predicted to be in that class, which means that 14% belongs to class 1, 38% to class 2 etc. Below that are the item percentages, which indicate the probability of a person belonging to that class to say that they liked the song, so for instance on Item 8, a person belonging to class 1 has an 8% chance of liking the song, class 2 a 31% chance of liking the song and a person belonging to class 3 a 16% chance of liking the song.
Judging by tables, it appears that the 3 classes can be interpreted as follows: A class that likes very little songs (class 1), a class that likes a lot of the songs (class 2) and a class that lies somewhere in between these 2 classes.
LCA class table
The LCA Class table
Column
ANOVA of Gold-MSI yields what we suspected
On the right you see the distribution of Gold-MSI scores per class, an ANOVA indicated that there was a difference between classes and post-hoc analysis with bonferonni correction showed this to be only probable for the classes 1 and 2.
Charts of class charateristics
```
Column
Conclusion
Under construction
Discussion
Under construction